• Journal of KIISE
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• v.43 no.12
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• pp.1334-1341
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• 2016

In recent years, the importance of managing software defects in the implementation stage has emerged because of the rapid development and wide-range usage of intelligent smart devices. Even if not a few studies have been conducted on the prediction models for software defects, their outcomes have not been widely shared. This paper proposes an efficient probabilistic management model of software metrics based on the Bayesian network, to overcome limits such as binary defect prediction models. We expect the proposed model to configure the Bayesian network by taking advantage of various software metrics, which can help in identifying improvements for refactoring. Once the source code has improved through code refactoring, the measured related metric values will also change. The proposed model presents probability values reflecting the effects after defect removal, which can be achieved by improving metrics through refactoring. This model could cope with the conclusive binary predictions, and consequently secure flexibilities on decision making, using indeterminate probability values.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.473-484
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• 2011

In this paper, we analyze and propose the Joint Call Admission Control(JCAC) scheme to combine network selection scheme and radio resource reservation based Call Admission Control(CAC) in LTE-WLAN heterogeneous networks. First, We propose the JCAC system that uses network decision rate to select a network for terminal and radio resource reservation scheme in overlaying LTE-WLAN network environment. And we analyze the performance of a proposed system using markov chain model. The performance is presented in terms of the new call blocking probability, handoff call dropping probability, and channel utilization of each network. As a performance result of the our research, the system using JCAC is better than the system using non-JCAC. We found a suitable resource reservation rate that is 10% in the system using JCAC. Our work may be useful as a guideline of resource reservation rate to introduce JCAC system using resource reservation scheme in overlaying LTE-WLAN network environment.

• Korea journal of population studies
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• v.34 no.3
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• pp.109-138
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• 2011

This study examines marriage between spouses from the same native place, suggests some stylized facts regarding the marriage type, and attempts to assess demographic, regional and economic factors which affect the probability of marriage between spouses from the same native place. Empirical analysis is carried out with original microdata on marriage over the period 1993-2009. Empirical results indicate that the birthplace of spouse played a less and less important role in marriage-related decision over time. Second, in addition to differences in a propensity to choose a person from the same native place as a spouse across regions, mobility and composition in population affected the probability of marriage between spouses from the same native place. For example, an influx of people into the capital region accelerated the chance of face-to-face communication between persons from the different birthplace, thereby decreasing the probability of marriage between spouses from the same native place. Finally, wider income gap between husband and wife led to lower probability of marriage between spouses from the same native place. To the best of our knowledge, this study is one of the first empirical analysis to investigate into the relationship between marriage and birthplace.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.2
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• pp.62-69
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• 2016

This paper proposes to select Measure of Performance(MOP) for object attainment in the counterfire operation and deduce the reasonable combination of blue force's hitting resources satisfying MOP's optimal value and regression equation for the object achievement time. Also, in the study-methodological perspective, a series of procedures for drawing the regression equation from the real world is presented. Firstly the model was made by simplifying the weapon-system information of red force and blue force, then the time for object attainment was derived from its simulation. Simulating the model for the counterfire operation was divided into three phases-detection, decision and hitting. The probability method by applying the random numbers were used for detection, fixed constant numbers for decision and hitting. The simulation was repeatedly performed to get the minimum time for the object attainment against the fixed enemy, and it was estimated as the optimal value of simulation. From this result, the optimum combination of blue force's weapon system against the red force and finally, the regression equation were obtained by using the response surface analyzing method in MINITAB. Thereafter this equation was completely verified by using 'the 2-sample t-test.' As a result, the regression equation is suitable.

• Smart Media Journal
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• v.11 no.2
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• pp.9-17
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• 2022

The purpose of this study is to implement a predictive model to support decision-making to replace a starting pitcher before a crisis situation in a baseball game. To this end, using the Major League Statcast data provided by Baseball Savant, we implement a predictive model that preemptively replaces starting pitchers before a crisis situation. To this end, first, the crisis situation that the starting pitcher faces in the game was derived through data exploration. Second, if the starting pitcher was replaced before the end of the inning, learning was carried out by composing a label with a replacement in the previous inning. As a result of comparing the trained models, the model based on the ensemble method showed the highest predictive performance with an F1-Score of 65%. The practical significance of this study is that the proposed model can contribute to increasing the team's winning probability by replacing the starting pitcher before a crisis situation, and the coach will be able to receive data-based strategic decision-making support during the game.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.19 no.4
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• pp.74-82
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• 2011

In order to enhance the aviation industry in Korea, many strategies have been published by some researchers as well as the government. However, considering the constrained conditions in real, since the ranking of their importance has not determined yet, they are difficult to be implemented by decision makers. Therefore, in terms of their demand for deciding the significance of strategies, the evaluation model of this paper was developed. In this study, the Cross-impact Hierarchy Process(CHP), an linked model of both the Analytic Hierarchy Process(AHP) and Cross Impact Analysis(CIA), was selected as the best model. That is because the strategies are not independent from each other, and one strategy can affect the others depending on its realization, which can be considered in CHP. To achieve our objective, at first, the strategies were categorized and arranged according to the evaluation structure. Secondly, the parameters such as conditional probability and weights were estimated from the survey conducted by 16 experts in the aviation field. Lastly, the result of the assessment were discussed, and further studies were suggested.

• Proceedings of the KSR Conference
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• 2007.11a
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• pp.1529-1532
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• 2007

Failure Mode, Effects, and Criticality Analysis (FMECA) is an extension of FMEA which includes a criticality analysis. The criticality analysis is used to chart the probability of failure modes against the severity of their consequences. The result highlights failure modes with relatively high probability and severity of consequences, allowing remedial effort to be directed where it will produce the greatest value. However, there are several limitations. Measuring severity of failure consequences is subjective and linguistic. Since The result of FMECA only gives qualitative and quantitative informations, it should be re-analysed to prioritize critical units. Fuzzy set theory has been introduced by Lotfi A. Zadeh (1965). It has extended the classical set theory dramatically. Based on fuzzy set theory, fuzzy logic has been developed employing human reasoning process. IF-THEN fuzzy rule based assessment approach can model the expert's decision logic appropriately. Fault tree analysis (FTA) is one of most common fault modeling techniques. It is widely used in many fields practically. In this paper, a simple fault tree analysis is proposed to measure the severity of components. Fuzzy rule based assessment method interprets linguistic variables for determination of critical unit priorities. An rail-way transforming system is analysed to describe the proposed method.

• Journal of Korea Multimedia Society
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• v.12 no.12
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• pp.1819-1826
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• 2009

To enhance the automatic performance of existing predicting and planning algorithms that require a predefined probability of the states' transition, this paper proposes a multiple sequence generation system. When interacting with unknown environments, a virtual agent needs to decide which action or action order can result in a good state and determine the transition probability based on the current state and the action taken. We describe a sequential behavior generation method motivated from the change in the agent's state in order to help the virtual agent learn how to adapt to unknown environments. In a sequence learning process, the sensed states are grouped by a set of proposed motivation filters in order to reduce the learning computation of the large state space. In order to accomplish a goal with a high payoff, the learning agent makes a decision based on the observation of states' transitions. The proposed multiple sequence behaviors generation system increases the complexity and heightens the automatic planning of the virtual agent for interacting with the dynamic unknown environment. This model was tested in a virtual library to elucidate the process of the system.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.167-176
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• 2005

This paper describes how the state tying model based on the decision tree which is one of Acoustic models used for speech recognition optimizes the model by reducing the number of mixture Gaussians of the output probability distribution. The state tying modeling uses a finite set of questions which is possible to include the phonological knowledge and the likelihood based decision criteria. And the recognition rate can be improved by increasing the number of mixture Gaussians of the output probability distribution. In this paper, we'll reduce the number of mixture Gaussians at the highest point of recognition rate by clustering the Gaussians. Bhattacharyya and Euclidean method will be used for the distance measure needed when clustering. And after calculating the mean and variance between the pair of lowest distance, the new Gaussians are created. The parameters for the new Gaussians are derived from the parameters of the Gaussians from which it is born. Experiments have been performed using the STOCKNAME (1,680) databases. And the test results show that the proposed method using Bhattacharyya distance measure maintains their recognition rate at $97.2\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. And the method using Euclidean distance measure shows that it maintains the recognition rate at $96.9\%$ and reduces the ratio of the number of mixture Gaussians by $1.0\%$. Then the methods can optimize the state tying model.

• Journal of Korean Society of Transportation
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• v.24 no.1 s.87
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• pp.19-28
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• 2006

To develop a crisis management for aviation safety, this study has defined crisis management includes risk management which is eliminates or lowers risks prior to accidents and emergency response after the accidents. This study takes a look at different kinds of crisis managements, risk managements and statistical methods of other nations and fields in order to develop a risk management model. Through surveys which have 102 risk factors that include air traffic control, maintenance and airport sectors, the weight of each risk factor was calculated and the probability was divided to develop a model for risk management. The risk management model of this study is conducted using four steps (risk management plan, risk factor identification, weight and probability analysis, decision making) and 4 standards of weight along with 5 standards of probability This study takes a look at Predictions through a quantitative method using a risk index for the risk management model An effective risk management model should have a wide and continuous collection of data and adopt various methods using this model. The crisis management could not be very effective only using a pre-active risk management. So it should also be conducted by using a pro-active response system to protect additional damage and to prevent accidents of the same nature. From the results, the most important points were the establishment of command and control accountabilities, and cooperation of related organizations.